FAQs
Do we support remote work?
This role is office-based and we do not offer remote-only roles; we value in-person collaboration at our Madrid office.
What technologies are primarily used in this role?
We mainly use Open Source frameworks like HuggingFace and LangChain, along with models such as Llama or Mixtral. Additionally, proficiency in Python, Docker, Kubernetes, and MLOps tools like Airflow and MLflow is required.
What are the main responsibilities of the DevOps Engineer in the Generative AI team?
Key responsibilities include designing and building infrastructure to host LLMs, owning deployment strategy for ML models, automating ML pipelines, managing Kubernetes deployments, developing observability best practices, and designing APIs for seamless integration of LLMs.
What qualifications are needed for this role?
Applicants should have 5+ years of professional experience as a DevOps Engineer, MLOps Engineer, ML Engineer, or Data Engineer, strong software development skills, proficiency in various tools and languages, and a solid understanding of DevOps best practices.
Is there a commitment to diversity and inclusion at Adyen?
Yes, Adyen emphasizes diversity, equity, and inclusion as crucial components of our workplace culture and encourages applicants from diverse backgrounds to apply.
What is the typical duration of the interview process?
The interview process typically takes about 4 weeks to complete, but this may fluctuate depending on the specific role.
What additional qualifications could be beneficial for this position?
Desirable additional qualifications include knowledge of ETL pipelines with PySpark and Airflow, end-to-end machine learning lifecycle understanding, and experience with Helm, Kustomize, and infrastructure as code tools like Terraform.
How can I contact you if I need flexibility during the application process?
You can let us know if you need more flexibility, and we will do our best to accommodate your needs during the application process.